Simon Zhang

Ph.D. student
Department of Computer Science
Purdue University
Email: zhan4125 AT purdue dot edu
GitHub

I am working on my Ph.D. of Computer Science at Purdue University.

I was a former Ph.D. student at the Ohio State University where I received my M.S. from the Department of Computer Science and Engineering.

I received my B.S. in Computer Science from Cornell University.

My research focus is in the areas of graph learning and algorithms, topological data analysis, and high performance computing. My advisor is Dr. Tamal Dey

I am currently interning at Argonne National Laboratory in the Data Science and Learning Division.

Publications

  • Simon Zhang, Soham Mukherjee, Tamal K. Dey "GEFL: Extended Filtration Learning for Graph Classification" to appear at the 1st Learning on Graphs Conference 2022

    •          GEFL  is released as open source on GitHub.

  • Tamal K. Dey, Simon Zhang "Approximating 1-Wasserstein Distance between Persistence Diagrams by Graph Sparsification" in 2022 Proceedings of SIAM Symposium on Algorithm Engineering and Experiments .

    •          PDoptFlow  is released as open source on GitHub.         

  • Simon Zhang, Mengbai Xiao, Hao Wang. "GPU-Accelerated Computation of Vietoris-Rips Persistence Barcodes" in Proceedings of the 36th Symposium on Computational Geometry.

    •          Ripser++  is released as open source on GitHub.

             SoCG 20 minute presentation slides

  • Simon Zhang, Mengbai Xiao, Chengxin Guo, Liang Geng, Hao Wang, Xiaodong Zhang. "HYPHA: a Framework based on Separation of Parallelisms to Accelerate Persistent Homology Matrix Reduction", in Proceedings of the 33rd ACM International Conference on Supercomputing.

    •          HYPHA  is released as open source on GitHub.

  • Yin Huai, Rubao Lee, Simon Zhang, Cathy H. Xia, Xiaodong Zhang. "DOT: a Matrix Model for Analyzing, Optimizing and Deploying Software for Big Data Analytics in Distributed Systems", Proceedings of the 2nd ACM Symposium on Cloud Computing.